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The template-based procedure of biorthogonal ternary wavelets for curve multiresolution processing

MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2019年第9期42卷 3255-3271页

作者： Li, Baobin Wang, Ning Li, Dengfeng Univ Chinese Acad Sci Sch Informat Sci Beijing Peoples R China Beijing Inst Elect Technol & Applicat Lab 4 Beijing Peoples R China Wuhan Text Univ Sch Math & Comp Wuhan 430200 Hubei Peoples R China

Curve multiresolution processing techniques have been widely discussed in the study of subdivision schemes and many applications, such as surface progressive transmission and compression. The ternary subdivision scheme is the more appealing one because it can possess the symmetry, smaller topological support, and certain smoothness, simultaneously. So biorthogonal ternary wavelets are discussed in this paper, in which refinable functions are designed for cure and surface multiresolution processing of ternary subdivision schemes. Moreover, by the help of lifting techniques, the template-based procedure is established for constructing ternary refinable systems with certain symmetry, and it also gives a clear geometric templates of corresponding multiresolution algorithms by several iterative steps. Some examples with certain smoothness are constructed.

关键词： biorthogonal ternary wavelet multiresolution processing template-based procedure ternary wavelet

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Novel technique for multiresolution color image segmentation

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OPTICAL ENGINEERING 2002年第3期41卷 608-614页

作者： Gao, JB Zhang, J Fleming, MG Univ Wisconsin Dept Elect Engn & Comp Sci Milwaukee WI 53201 USA Med Coll Wisconsin Dept Dermatol Milwaukee WI 53209 USA

We describe a novel technique for color image segmentation. This technique includes three components: a color space transformation, Markov random field expectation-maximization (MRF-EM) segmentation, and a multiresolution implementation termed "narrow band." The color space transformation, from RGB to LUV, contributes to a perceptually reasonable segmentation result. The MRF-EM algorithm enables unsupervised segmentation and enforces a region smoothness constraint. The narrow-band, multiresolution implementation confines fine resolution processing to a small fraction of the image, thereby achieving acceleration over traditional multiresolution schemes. Experimental results with medical and TV images demonstrate the efficacy of the proposed technique. (C) 2002 Society of Photo-Optical Instrumentation Engineers.

关键词： image segmentation color image segmentation multiresolution processing Markov random fields mean field theory image analysis

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Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

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IEEE TRANSACTIONS ON IMAGE processing 2005年第6期14卷 770-782页

作者： Zavorin, I Le Moigne, J Univ Maryland Baltimore Cty Goddard Earth Sci & Technol Ctr Catonsville MD 21228 USA NASA Goddard Space Flight Ctr Appl Informat Sci Branch Greenbelt MD 20771 USA

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

关键词： gradient-based optimization image registration multiresolution processing remote-sensing imagery wavelets

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Image compression and denoising using multiresolution region-based image description scheme

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JOURNAL OF SUPERCOMPUTING 2023年第4期79卷 4243-4265页

作者： Zhao, Yanjun Belkasim, Saeid Aubry, Guillaume Troy Univ Coll Arts & Sci Troy AL 36082 USA Georgia State Univ Coll Arts & Sci Atlanta GA 30303 USA Georgia Inst Technol Coll Engn Atlanta GA 30332 USA

Lossy image compression removes redundant information which considerably reduces the size of files needed for storing images. Lossy compression at different resolutions can be used to remove redundant information at each resolution level. Wavelet transform is one of the most successful multiresolution tools that has been widely applied in image compression. However, wavelet transform suffers from high computational complexity. In this paper, we propose a novel multiresolution region-based image description scheme that can be used to transform any region-based image descriptor into a multiresolution structure. Our proposed multiresolution scheme uses the original image information independently from other preprocessing techniques such as filtering, region segmentation, or any prior assumptions that might result in an additional computational overhead. The tree structure of our multiresolution scheme is well suited for parallel processing, which further improves its computational efficiency. Based on this multiresolution scheme, we propose a novel image compression and denoising scheme that can compress and denoise images simultaneously. Our image compression and denoising scheme achieves multiresolution analysis and avoids blocking artifacts;it has high computational accuracy and efficiency as well as strong flexibility.

关键词： Image compression Image denoising multiresolution descriptors multiresolution processing

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Fast indoor scene description for blind people with multiresolution random projections

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2017年 44卷 95-105页

作者： Mekhalfi, Mohamed L. Melgani, Farid Bazi, Yakoub Alajlan, Naif Univ Trento Dept Informat Engn & Comp Sci Via Sommarive 9 I-38123 Trento Italy King Saud Univ Coll Comp & Informat Sci Riyadh 11543 Saudi Arabia

Object recognition forms a substantial need for blind and visually impaired individuals. This paper proposes a new multiobject recognition framework. It consists of coarsely checking the presence of multiple objects in a portable camera-grabbed image at a considered indoor site. The outcome is a list of objects that likely appear in the indoor scene. Such description is meant to uplift the conscience of the blind person in order to better sense his/her surroundings. The method consists of a library containing (i) a bunch of images represented by means of the Random Projections (RP) technique and (ii) their respective list of objects, both prepared offline. Thus, given an online shot image, its RP representation is generated and matched to the RP patterns of library images. It thus inherits the objects of the closest image from the library. Extensive experiments returned promising recognition accuracies and a processing lapse of real-time standard.(C) 2017 Elsevier Inc. All rights reserved.

关键词： Assistive technologies Coarse scene description Multiobject recognition multiresolution processing Random projection Visually impaired people

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Hierarchical statistical models for the fusion of multiresolution image data

Hierarchical statistical models for the fusion of multiresol...

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Conference on Neural, Morphological, and Stochastic Methods in Image and Signal processing

作者： LAFERTE, JM HEITZ, F PEREZ, P FABRE, E INST RECH INFORMAT & SYST ALEATOIRES F-35042 RENNESFRANCE

ISBN: (纸本)0819419273

This paper presents a class of nonlinear hierarchical algorithms for the fusion of multiresolution image data in low-level vision. The approach combines nonlinear causal Markov models defined on hierarchical graph structures, with standard Bayesian estimation theory. Two random processes defined on simple hierarchical graphs (quadtrees or 'ternary graphs') are introduced to represent the multiresolution observations at hand and the hidden labels to be estimated. Two optimal algorithms (inspired from Viterbi's algorithm) are developed on the quadtree structure. The first one gives the exact solution for the MAP (maximum a posteriori) estimator. The second one gives, on the same structure, the global minimum of an energy function more relevant than the MAP criterion. These algorithms are noniterative, estimates being obtained within two passes on the graph structure. They are compared to an extension of the multiscale algorithm proposed by Bouman et al. which is adapted here to multiresolution data fusion.

关键词： FUSION MARKOV MODELS multiresolution processing BAYESIAN ESTIMATION VITERBI ALGORITHMS

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multiresolution binary optical correlator using the wavelet transform

Multiresolution binary optical correlator using the wavelet ...

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Conference on Photonic Device Engineering for Dual-Use Applications

作者： Kozaitis, SP FLORIDA INST TECHNOL DIV ELECT COMP SCI & ENGNMELBOURNEFL 32901

ISBN: (纸本)081941834X

We used morphological filters to approximate wavelet scaling functions for multiresolution processing of an image. Because some spatial light modulators (SLMs) can only display binary data, wavelet processing of binary images is inhibited. Therefore, we considered an alternative way - morphological processing - to generate a wavelet representation that consists entirely of binary elements. The effects of these filters are dependent on the input signal and cannot be generalized. Therefore, we used a statistical approach to approximate the scaling functions or various wavelets using morphological filters.

关键词： multiresolution processing morphology optical correlator wavelet transform

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SCALE-BASED DETECTION OF CORNERS OF PLANAR CURVES

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1992年第4期14卷 430-449页

作者： RATTARANGSI, A CHIN, RT UNIV WISCONSIN DEPT ELECT & COMP ENGN MADISON WI 53706 USA

A technique for detecting and localizing corners of planar curves is proposed. The technique is based on Gaussian scale space, which consists of the maxima of absolute curvature of the boundary function presented at all scales. The scale space of isolated simple and double corners is first analyzed to investigate the behavior of scale space due to smoothing and interactions between two adjacent corners. The analysis shows that the resulting scale space contains line patterns that either persist, terminate, or merge with a neighboring line. Next, the scale space is transformed into a tree that provides simple but concise representation of corners at multiple scales. Finally, a multiple-scale corner detection scheme is developed using a coarse-to-fine tree parsing technique. The parsing scheme is based on a stability criterion that states that the presence of a corner must concur with a curvature maximum observable at a majority of scales. Experiments were performed to show that the scale space corner detector is reliable for objects with multiple-size features and noisy boundaries and compares favorably with other corner detectors tested.

关键词： CORNER DETECTION CURVATURE SCALE SPACE DIGITAL CURVES DOMINANT POINT DETECTION GAUSSIAN SMOOTHING multiresolution processing SCALE SPACE FILTERING

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AUDITORY REPRESENTATIONS OF ACOUSTIC-SIGNALS

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IEEE TRANSACTIONS ON INFORMATION THEORY 1992年第2期38卷 824-839页

作者： YANG, XW WANG, K SHAMMA, SA UNIV MARYLAND DEPT ELECT ENGNCOLLEGE PKMD 20742

An analytically tractable framework is presented to describe mechanical and neural processing in the early stages of the auditory system. Algorithms are developed to assess the integrity of the acoustic spectrum at all processing stages. The algorithms employ wavelet representations, multiresolution processing, and the method of convex projections to construct a close replica of the input stimulus. Reconstructions using natural speech sounds demonstrate minimal loss of information along the auditory pathway. Furthermore, close inspection of the final auditory patterns reveal spectral enhancements and noise suppression that have close perceptual correlates. Finally, the functional significance of the various auditory processing stages are discussed in light of the model, together with their potential applications in automatic speech recognition and low bit-rate data compression.

关键词： AUDITORY SYSTEM multiresolution processing WAVELET TRANSFORM CONVEX PROJECTIONS

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CONTRAST ENHANCEMENT OF MEDICAL IMAGES USING MULTISCALE EDGE REPRESENTATION

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OPTICAL ENGINEERING 1994年第7期33卷 2151-2161页

作者： LU, JA HEALY, DM WEAVER, JB DARTMOUTH COLL DEPT MATH & COMP SCIHANOVERNH 03755 DARTMOUTH COLL HITCHCOCK MED CTRDEPT DIAGNOST RADIOLHANOVERNH 03756

Experience suggests the existence of a connection between the contrast of a gray-scale image and the gradient magnitude of intensity edges in the neighborhood where the contrast is measured. This observation motivates the development of edge-based contrast enhancement techniques. We present a simple and effective method for image contrast enhancement based on the multiscale edge representation of images. The contrast of an image can be enhanced simply by stretching or upscaling the multiscale gradient maxima of the image. This method offers flexibility to selectively enhance features of different sizes and ability to control noise magnification. We present some experimental results from enhancing medical images and discuss the advantages of this wavelet approach over other edge-based techniques.

关键词： ADAPTIVE WAVELET TRANSFORMS CONTRAST ENHANCEMENT multiresolution processing MULTISCALE EDGES MEDICAL IMAGE processing

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